Object detection(OD)in remote sensing images(RSI)acts as a vital part in numerous civilian and military application areas,like urban planning,geographic information system(GIS),and search and rescue *** recognition fr...
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Object detection(OD)in remote sensing images(RSI)acts as a vital part in numerous civilian and military application areas,like urban planning,geographic information system(GIS),and search and rescue *** recognition from RSIs remained a challenging process because of the difficulty of background data and the redundancy of recognition *** latest advancements in deep learning(DL)approaches permit the design of effectual OD *** study develops an Artificial Ecosystem Optimizer with Deep Convolutional Neural Network for Vehicle Detection(AEODCNN-VD)model on Remote Sensing *** proposed AEODCNN-VD model focuses on the identification of vehicles accurately and *** detect vehicles,the presented AEODCNN-VD model employs single shot detector(SSD)with Inception network as a baseline *** addition,Multiway Feature Pyramid Network(MFPN)is used for handling objects of varying sizes in *** features from the Inception model are passed into theMFPNformultiway andmultiscale feature ***,the fused features are passed into bounding box and class prediction *** enhancing the detection efficiency of the AEODCNN-VD approach,AEO based hyperparameter optimizer is used,which is stimulated by the energy transfer strategies such as production,consumption,and decomposition in an *** performance validation of the presentedmethod on benchmark datasets showed promising performance over recent DL models.
Graph Neural Networks (GNNs) have shown efficacy in graph node classification, but face computational challenges on large-scale graphs. Although existing graph reduction methods address these issues, they still requir...
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Semantic dictionaries are the basis of natural language processing tasks. With the construction of WordNet, CCD, HowNet and other semantic dictionaries, the semantic resources of Chinese and English have been greatly ...
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This study compares microstrip antennas, microstrip antenna arrays, and slotted microstrip antenna arrays for 5G communication. Emphasizing the compact size and compatibility with 5G devices, microstrip antennas are e...
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Content authentication,integrity verification,and tampering detection of digital content exchanged via the internet have been used to address a major concern in information and communication *** this paper,a text zero...
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Content authentication,integrity verification,and tampering detection of digital content exchanged via the internet have been used to address a major concern in information and communication *** this paper,a text zero-watermarking approach known as Smart-Fragile Approach based on Soft Computing and Digital Watermarking(SFASCDW)is proposed for content authentication and tampering detection of English text.A first-level order of alphanumeric mechanism,based on hidden Markov model,is integrated with digital zero-watermarking techniques to improve the watermark robustness of the proposed *** researcher uses the first-level order and alphanumeric mechanism of Markov model as a soft computing technique to analyze English ***,he extracts the features of the interrelationship among the contexts of the text,utilizes the extracted features as watermark information,and validates it later with the studied English text to detect any *** has been implemented using PHP with VS code *** robustness,effectiveness,and applicability of SFASCDW are proved with experiments involving four datasets of various lengths in random locations using the three common attacks,namely insertion,reorder,and *** SFASCDW was found to be effective and could be applicable in detecting any possible tampering.
This study focuses on improving "Content-Based Image Retrieval" (CBIR) systems through the utilization of optimized convolutional neural network (CNN) models. Traditionally, CBIR relied on text-based approac...
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Water pipeline leaks pose significant risks to urban infrastructure, leading to water wastage and potential structural damage. Existing leak detection methods often face challenges, such as heavily relying on the manu...
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Medical image analysis plays an irreplaceable role in diagnosing,treating,and monitoring various *** neural networks(CNNs)have become popular as they can extract intricate features and patterns from extensive *** pape...
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Medical image analysis plays an irreplaceable role in diagnosing,treating,and monitoring various *** neural networks(CNNs)have become popular as they can extract intricate features and patterns from extensive *** paper covers the structure of CNN and its advances and explores the different types of transfer learning strategies as well as classic pre-trained *** paper also discusses how transfer learning has been applied to different areas within medical image *** comprehensive overview aims to assist researchers,clinicians,and policymakers by providing detailed insights,helping them make informed decisions about future research and policy initiatives to improve medical image analysis and patient outcomes.
The rapid expansion of IoT technologies like smart sensors and home appliances is likely to have far-reaching consequences. Connectivity, ubiquitous presence, and low computational power are the hallmarks of IoT gadge...
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Lightning strikes on the catenary will cause a sharp rise in rail potential, which directly threatens the safety of the signal equipment connected to the rail along the trackside. It is urgent to carry out research on...
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